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Popular mid-level AI role with broad stack requirements and metro appeal increases candidate competition.
ML/AI engineering skills with Azure-specific tools and enterprise integrations yield medium transferability across industries.
Explicit 3–5 years plus mandatory Azure OpenAI, CI/CD, IaC, and programming skills create strict shortlisting filters.
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Own end-to-end delivery of AI initiatives including data preparation, pipeline design, deployment, and support for production-ready AI and LLM-based applications.
Design and implement reliable, scalable AI agents and applications integrated with enterprise APIs, data sources, and services.
Build and manage prompt pipelines, automated testing, telemetry, safety checks, CI/CD, and evaluate practical outcomes like adoption and defect reduction.
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
3 to 5 years of software engineering experience focused on AI, automation, backend services, or integrations.
Hands-on experience with Generative AI, Azure AI Foundry/Studio, Azure OpenAI, vector retrieval, or agent frameworks.
Strong programming skills in .NET/C#, Python, or TypeScript; experience with REST/GraphQL APIs, test automation, CI/CD, and infrastructure as code (Terraform/Bicep).
Experienced AI engineer capable of taking AI prototypes to scalable production solutions with full lifecycle ownership.
Practitioner with strong integration skills across data pipelines, enterprise APIs, and backend services in cloud environments.
Detail-oriented professional focused on automation, testing, secure software delivery, and practical business impact measurement.